What does it all mean?

Just over a quarter of a century ago, my friend and colleague Steve Juggins and a group of other palaeoecologists came up with a clever way to relate the composition of diatom samples taken from different levels of a sediment core to the environmental conditions of the lake at the time that these diatoms were alive.   At the heart of this was a set of statistical tools called “transfer functions” and the use of these has proliferated over subsequent years, spilling from diatoms to many other groups of organisms and from palaeoecological studies to contemporary investigations of man’s impact on the environment.   So pervasive have these methods become that Steve returned to the subject a few years ago and critiqued the many misuses of the method that he was seeing in the literature.

The principle behind the use of transfer functions is that each species has a characteristic response to an environmental pressure gradient (in early studies this was pH) which could be portrayed as a unimodal (approximately bell-shaped curve).   The point along the gradient where a species is most abundant represents the “optimum” condition, the level of the pressure where the species thrives best.  The average of the optima of all organisms in a sample, Steve and colleagues showed, could be then used to estimate the value of the pressure.   This unlocked the door to quantitative reconstructions of changes in acidification of lakes in the UK and Scandinavia that, in turn, ultimately shaped environmental policy. It was one of the most impressive achievements of applied ecologists in the 20th century.

A diagrammatic representation of the principle behind transfer functions: each organism has a characteristic response to the predominant pressure (nutrient/organic pollution in this case).

Part of the reason for their success in building strong predictive models was, I suspect, that the pollutant that they were focussed upon had a direct effect on the physiology of the cells which, in turn, created strong selective pressures on the community.   Another reason was that palaeoecological samples condense all the habitat variation within a lake (plankton v benthic, seasonal differences etc) into a single assemblage.   This, then, begs the question of how well we should expect transfer functions to perform when applied to assemblages which represent much narrower windows of space and time, and when the pollutants of interest exert indirect rather than direct effects on the organisms.   Or, to recast that question another way, are some of the problems we encounter interpreting diatom indices from rivers another form of the misuse of transfer functions that Steve dissects in his review?

It is easy to believe that transfer functions do work when applied to contemporary diatom assemblages from rivers.   If you evaluate datasets you will almost certainly find that the “optima” for all the species do appear to be arranged along a continuum along the pressure gradient.  The question that we need to ask is whether this represents a causal relationship or is just a statistical artefact?  I touched on this issue in “What we expect is often what we get …” but, in that post, I was mostly interested in how samples react along a gradient, not the response of individual species.  I suspect that, given the importance of alkalinity in freshwater algal ecology (see “Ecology in the Hard Rock Café”), this must influence the distribution of optima along a nutrient gradient.   This will be compounded when sample sizes are small, as the likelihood is that the sample optimum will not correspond exactly to the “true” optimum for the species in question (a question Steve has also addressed in a more recent paper – see reference list below).  Finally, this is all embedded within a larger problem: that most of the work I have discussed here involves statistical inference from datasets compiled from samples collected from a range of sites in a region, but is intended to address changes in time rather than space (so-called “space-for-time substitution – see reference by Pickett below).   There has been relatively little testing of species preferences under controlled experimental conditions.

In practice, I suspect, the physiological response of benthic algae to nutrients is less complicated than our noisy graphs suggest.   I set out a version of this in “What we expect is often what we get …”.   That post dealt primarily with communities of microalgae; this is the same basic scheme (with some slight revisions) but posed in terms of the physiological response of the organisms.  It borrows from the habitat matrix conceptual model of Barry Biggs, Jan Stevenson and Rex Lowe (which, itself, builds on earlier work on terrestrial plants by Phil Grime and colleagues).

An alternative explanation for the response of benthic algae to nutrients and organic pollution.  a., b., c. and d. are explained in the text.

  1. Low nutrients / high oxygen concentrations – the “natural state” in most cases. Biggs et al. referred to species adapted to such conditions “stress-adapted” as they can cope in situations where nutrients are scarce. Associated with TDI scores 1 and 2.  Examples: Hannaea arcus, Achnanthidium minutissimum, Tabellaria flocculosa.
  2. high nutrients / no “secondary effects” of eutrophication – these are “competitive” species in Biggs et al.’s template and can thrive when there is anthropogenic enrichment of nutrients. Ideally, this group would consist of species that have a physiological adaptation that allows them to thrive when nutrients are plentiful though, in practice, our understanding is based mostly on inference from spatial patterns. The “window” where such species can thrive is wide, and will overlap with the two states described below, in many cases.  Associated with TDI scores 3 and 4.  Examples: Amphora pediculus, Rhoicosphenia abbreviata, Cocconeis pediculus.  Cladophora glomerata would be a good example of a non-diatom that belongs to this group.
  3. high nutrients plus “secondary effects” of eutrophication – this category extends the habitat template of Biggs et al. to include organisms whose are reacting to secondary effects  of nutrient enrichment (e.g. shade and low oxygen) rather than to the elevated nutrients per se and is, consequently, difficult to differentiate from a direct response to organic pollution. Associated with TDI scores 4 and 5. Examples include several species of Nitzschia as well as Mayamaea and Fistulifera, amongst others.   Importantly, this group may co-exist with representatives from group b. – perhaps inhabiting different zones of the biofilm that typically blend together when a sample is taken.
  4. high nutrients / very low oxygen – a final category that represents extreme situations when an ability to cope with reducing conditions is beneficial, and where diatoms that are facultative heterotrophs may thrive. Associated with TDI score 5. Heterotrophic fungal and bacterial growths (“sewage fungus”) may also be abundant.  Once again, there is likely to be some overlap between this and other groups.   Technically, this group is more likely to be associated with serious organic pollution than with nutrients; however, it will be found at sites where nutrient concentrations are high and it is possible that an association with nutrients may be inferred from spatial patterns.

We are left, in other words, with a choice between deriving optima along a continuous scale based on inferences from spatial patterns within which we know that there are significant confounding variables or dividing species into a few physiologically-defined categories for which there is not very much experimental underpinning.   Neither is ideal, and some of our recent analyses suggest that, in terms of model strength, there is little to choose between them.   The former, in my view, suggests an artificially high level of precision that is unrealistic, given the current state of knowledge.   The latter, on the other hand, links the data to a conceptual model rather than simply relying upon the numbers that squirt out at the far end of a statistical process.

That does not mean that such an approach might not be appropriate for some other groups of organisms.  The reason why I urge simplicity for diatoms is largely because of the scale of the habitats that we are sampling, in relation to the wider patterns of variability.  A continuous series of optima may be appropriate in some cases too.   Macrophytes surveys, for example, encompass all visible organisms found along a 100 m stretch.   These will have a range of life history and nutrient acquisition strategies: some of these will take up nutrients from the water, some from the sediments.  Different types of sediment will vary in the supply of phosphorus and nitrogen, and so on.   There will still be issues of confounding variables and risks of inferring from correlative rather than causal relationships, but perhaps the overall patchiness experienced over the survey length will create a more complex web of interactions between nutrients and community that justifies a continuous scale.

For diatoms, however, simplicity is probably the best choice.   In the absence of definitive evidence one way or the other we apply Occam’s Razor (“entities should not be multiplied unnecessarily”) and opt for the simpler of the two hypotheses pending evidence to the contrary.   This, in turn, may address a deeper issue: that of finding robust answers to complex problems (see “Unravelling causal thickets …”).   Inference from statistical models is only as good as the conceptual models that underpin those models and, I fear, we too often are so lost in the detail of the many confounding variables that we lose sight of our goals.  Being able to understand our observations in terms of ecological process is the first step to finding robust solutions to our problems.

References

Bennion, H., Juggins, S. & Anderson, N.J. (1996).  Predicting epilimnetic phosphorus concentrations using an improved diatom-based transfer function and its application to lake eutrophication management. Environmental Science & Technology 30: 2004-2007.

Biggs, B.J.F., Stevenson, R.J. & Lowe, R.L. (1991). A habitat matrix conceptual model for stream periphyton. Archiv für Hydrobiologie 143: 21-56.

Birks, H.J.B.,  Line, J.M., Juggins, S., Stevenson, A.C. & ter Braak, C.J.F.  (1990). Lake surface-water chemistry reconstructions from palaeolimnological data. Diatoms and pH reconstruction. Philosophical Transactions of the Royal Society of London Series B 327: 263-278.

Juggins, S. (2013).  Quantitative reconstructions in palaeolimnology: new paradigm or sick science?  Quaternary Science Reviews 64: 20-32.

Kelly, M.G., King, L. & Ní Chatháin, B. (2009).  The conceptual basis of ecological status assessments using diatoms.  Biology and Environment: Proceedings of the Royal Irish Academy 109B: 175-189.

Pickett, S.T.A. (1988).  Space-for-time substitution as an alternative to long-term studies.  Pp. 110-135.   In: Long-term Studies in Ecology: Approaches and Alternatives (edited by G.E.. Likens).  Springer-Verlag, New York.

Reavie, E.D. & Juggins, S. (2011).  Exploration of sample size and diatom-based indicator performance in three North American phosphorus training sets.  Aquatic Ecology 45: 529-538.

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The challenging ecology of a freshwater diatom?

amp_pedi_pollybrook

Amphora pediculus from Polly Brook, Devon, December 2016. Scale bar: 10 micrometres (= 1/100th of a millimetre).

The images above show one of the commonest diatoms that I find in UK waters.  It is a tiny organism, often less than 1/100th of a millimetre long, which means that it tests the limits of the camera on my microscope.  In recent months, however, it is not just the details on Amphora pediculus’ cell wall that I am struggling to resolve: I also find myself wondering how well we really understand its ecology.

The received wisdom is that Amphora pediculus favours hard water, does not like organic pollution and is relatively tolerant of elevated concentrations of inorganic nutrients.  This made it a very useful indicator species in a period of my career when we were using diatoms to identify sewage work s where investment in nutrient-removal technology might yield ecological benefits.  There were many nutrient-rich rivers, particularly in the lowlands, where any sample scraped from the upper surface of a stone was dominated by these tiny orange-segment-shaped diatom valves.   Unfortunately, twenty years on, many of those same rivers have much lower concentrations of nutrients (see “The state of things, part 2”) but still have plenty of Amphora pediculus.   Did I get the ecology of this species wrong?

The graph below shows some data from the early- and mid- 1990s showing how the abundance of Amphora pediculus was related to phosphorus.   The vertical lines on this graph show the average position of the boundaries between phosphorus classes based on current UK standards.   Records for A. pediculus are clustered in the “moderate” and “poor” classes, supporting my initial assertion that this species is a good indicator of nutrient-enriched conditions, but there are also samples outside this range where it is also abundant, so A. pediculus is only really useful when it is one of a number of strands of evidence.

aped_v_p

The relationship between Amphora pediculus and reactive phosphorus in UK rivers, based on data collected in the early-mid 1990s.  Vertical lines show the average boundaries between high and good (blue), good and moderate (green), moderate and poor (orange) and poor and bad (red) status classes based on current UK standards and the two arrows show the optima based on this dataset (right) and data collected in the mid-2000s (left).

If we weight each phosphorus measurement in the dataset by the proportion of Amphora pediculus at the same site (i.e. so that sites where A. pediculus is abundant are given greater weight), we get an idea of the point on the phosphorus gradient where A. pediculus is most abundant.   We can then infer that this is the point at which conditions are most suitable for the species to thrive.  In ecologist’s shorthand, this is called the “optimum” and, based on these data, we can conclude that the optimum for A. pediculus is 154 ug L-1 phosphorus.  The right hand arrow indicates this point on the graph below. However, I then repeated this exercise using another, larger, dataset, collected in the mid-2000s.   This yielded an optimum of 57 ug L-1 phosphorus (the left hand arrow on the graph), less than half of that suggested by the 1990s dataset.   There are, I think, two possible explanations:

First, the 1990s phosphorus gradient was based on single phosphorus samples collected at the same time that the diatom sample was collected (mostly spring, summer and autumn) whilst the mid-2000s phosphorus gradient was based (mostly) on the average of 12 monthly samples.  As phosphorus concentrations, particularly in lowland rivers, tend to be higher in summer than at other times of the year, it is possible that part of the difference between the two arrows is a result of different approaches.  (For context, in the 1990s, when I first started looking at the effect of nutrients in rivers, phosphorus was not routinely measured in many rivers, so we had no option but to do the analyses ourselves, and certainly did not have the budget or time to collect monthly samples).

However, another possibility is that the widespread introduction of phosphorus stripping in lowland rivers in the period between the mid-1990s and mid-2000s means that the average concentration of phosphorus in the rivers where conditions favour Amphora pediculus have fallen.   In other words, A. pediculus is tolerant of high nutrient conditions but is not that bothered about the actual concentration.   My guess is that it thrives under nutrient-rich conditions so long as the water is well-oxygenated and, as biochemical oxygen demand is generally falling, and dissolved oxygen concentrations rising (see “The state of things, part 1”), this criterion, too is widely fulfilled.   I suspect that both factors probably contribute to the change in optima.

But the second point in particular raises a different challenge:  We often slip into casual use of language that implies a causal relationship between a pressure such as phosphorus and biological variables whereas, in truth, we are looking at correlations between two variables.   Causal relationships are, in any case, quite hard to establish and the effect that we call “eutrophication” is really the result of interactions between a number of factors acting on the biology.   All of these simplifications mean that it is useful, from time to time, to look back to see if assumptions made in the past still hold.   In this case, I suspect that some of our indices might need a little fine-tuning.  There is no disgrace in this: the evidence we had in the 1990s led us to both to a conclusion about the relative sensitivity of Amphora pediculus to nutrients but also fed into a large-scale “natural experiment” in which nutrient levels in UK rivers were steadily reduced.   When we evaluate the results of that natural experiment we see we need to adjust our hypotheses.  That’s the nature of science.  As the sign on the door of a friend who is a parasitologist reads: “if we knew what we were doing, it wouldn’t be research”.

References

The 1990s dataset (89 records) is mostly based on data used in:

Kelly M.G. & Whitton B.A. (1995).   A new diatom index for monitoring eutrophication in rivers.   Journal of Applied Phycology 7: 433-444.

The mid-2000s dataset (1145 records) comes from:

Kelly, M.G., Juggins, S., Guthrie, R., Pritchard, S., Jamieson, B.J., Rippey, B, Hirst, H & Yallop, M.L. (2008).   Assessment of ecological status in UK rivers using diatoms.   Freshwater Biology 53: 403-422.

The camera never lies?

ehen_sc_160906

The picture above shows a rather unprepossessing view of a river bed, photographed earlier this month.   The stones, to give a sense of scale, are all less than ten centimetres across.    What is your immediate reaction?   My guess is that it is probably negative: that mass of green filaments cannot indicate a healthy ecosystem.   However, the next picture is a view of the same river bed photographed a month earlier and that shows a very different scene.  There are just a few tufts of filamentous algae, if you look closely but, overall, the stones are clean.   First impressions, at least, are not negative.

That phrase “first impressions” is important.   If you were to take a closer look at the composition of the plants and animals at this site, you will see little to cause concern.  There is a good diversity of algae and invertebrates, and these include several that thrive only in high quality rivers.   The larger plants, too, are those that we associate with rivers with low nutrient concentrations and there are also salmon and trout present.   There are issues with the river but these are not my primary concern today.  What is of interest to me today is the reason behind the negative reaction.

ehen_sc_160809

The same river bed as the upper photograph, but photographed in August 2016, rather than September 2016.  Both photographs taken on an Olympus  TG2 camera.

There is a trend for pictures such as the one above to be included in reports.  The reason is, I think, quite straightforward: waterproof digital cameras of a reasonable quality are now sufficiently affordable that many of us carry them about as standard parts of our field kit.  They are useful for documenting many different aspects of the aquatic world but I worry that the audiences for these pictures have few opportunities to calibrate their experiences.

The contrast between the two pictures illustrates the danger of relying on a single photograph to infer the condition of a stream or lake.   Many types of aquatic survey may take place annually; a picture in a report can, therefore, never be wholly representative of the state of algae at a site, as quantities can change rapidly.   Inferring the condition of a water body from a short-lived fast-responding group of organisms is never straightforward and depends upon those interpreting the data (and, in this instance, visual evidence) being able to place this into context.  I worry when I see pictures such as those above included in reports of surveys of aquatic plants, in particular, because surveyors are used to studying organisms with longer life-cycles and more stable assemblages.   A photograph of mass algal growths offers a “snapshot” with few guarantees that this is typical for the the lake or stream under consideration.   The reality is that the beds of even healthy streams turn green for brief periods during the year; the problem for the surveyor unversed in algal lore, is how to separate “signal” from “noise”.

Some of my earlier posts have demonstrated the advantages that a close-up view of the underwater world that these cameras offer to freshwater biologists (see “Bollihope Burn in close-up”).   We are in a better place through having the ability to record the underwater world directly, rather than simply naming, counting and measuring; photography gives us a higher level cognitive experience and a more holistic overview of systems.  But these rewards are accompanied by new challenges.   In the same way that Wikipedia is an asset, only if used with safeguards to ensure that information that is presented can be verified; therefore we need to treat photographs of the underwater world with respect.   As for most of our technological advances, they complement, rather than replace, existing knowledge and wisdom.

Everything is connected …

I’ve written about a curious group of algae called stoneworts (or charophytes) on a couple of occasions (see “The desert shall rejoice and bloom” and “Croft Kettle through the magnifying glass”. The significance of the name “stonewort” becomes obvious when you pick up a Chara plant, expecting it to be soft and pliable, and are struck by the rough texture of the axes, caused by the deposition of lime.

Stonewort-Chara-hisp-macro_

Chara hispida, photographed by Chris Carter.   Note the main axis and branches, from which whorls of branchlets arise at intervals.

The stoneworts are asssociated with hard water, so this deposition should not be a great surprise (the process by which kettles are coated with lime scale in hard water areas is very similar) however, most of the other plants in these habitats don’t share this property, so what is so special about Chara?   The answer is that, in hard waters, the carbon dioxide that plants need for photosynthesis is in short supply, but much more carbon is available as the bicarbonate ion.   Some aquatic plants can absorb the bicarbonate and then use an enzyme, carbonic anhydrase, to convert this bicarbonate to carbon dioxide. Chara, however, has a different strategy, actively pumping out hydrogen from inside the cells which, in turn, react with the bicarbonate and release carbon dioxide, which can then be absorbed by the plant.   However, as the water is also rich in calcium, a further series of reactions produces insoluble calcium carbonate, generating some additional carbon dioxide in the process As this series of reactions occurs very close to the cells from which the hydrogen ions are leaking, the precipitates end up on the plant surface, creating the rough texture.   The chemistry is way beyond this blog (meaning “… this blogger”) but you can follow it up in the references below.

Stonewort-Chara-intermedia-

Marcroscopic view of Chara intermedia showing an internode with a whorl of branchlets, along with spine cells and cortex cells (photograph: Chris Carter).

Another ion that is not very soluble is phosphate and this often gets caught up with the precipitating lime to form calcium phosphate.   This can be beneficial, as this phosphorus might otherwise fuel growth of phytoplankton which, in turn, would shade the Chara.   This means that Chara meadows should be resilient to artificial enrichment of nutrients to a limited extent at least.   However, there is some evidence that this capacity might be much less than was previously thought.   Hawes Water, a small tarn in Lancashire (not to be confused with Haweswater in Cumbria), for example, used to have rich and diverse communities of Chara spp, even in the deepest parts, but now the Chara and other submerged aquatic plants are confined to the shallow margins of the lake.   There is also good evidence of artificial enrichment in this catchment. The surprise is that concentrations of phosphorus in the water are still relatively low, yet the Chara meadows are much reduced compared with their condition fifty years ago.   The team that did this work also looked at another small marl lake, Cunswick Tarn, near Kendal in Cumbria, and found very similar changes.

It suggests a sensitivity to eutrophication that, perhaps, has previously been under-estimated, but it also points to the importance of balancing mechanisms in nature. On the one hand, Chara has some inbuilt capacity to counter-act increased nutrient concentrations. But others have shown that the ability of Chara to precipitate calcium carbonate is, itself, based on the photosynthesis rate.   The Chara meadows will reach a point when their natural capacity to absorb this extra phosphorus will be exhausted and then, as the phytoplankton take advantage of this, the water will get more turbid, reducing the amount of light reaching the Chara.   Less light means less photosynthesis and that will reduce the need for bicarbonate and, in turn, mean less carbonate deposition and less phosphorus removed. The evidence from Hawes Water is that this change happens very quickly: an ecological “domino effect”, if you like. As ever, everything is connected; sometimes in surprising ways.

Chara-virgata-Skye-fruit

Chara virgata (with oospores) from the Isle of Skye, photographed by Chris Carter.

Reference

McConnaughey, T. (1991). Calcification in Chara corallina: CO2 hydroxylation generates protons for bicarbonate assimilation. Limnology and Oceanography 619-628.

Pentecost, A. (1984). The growth of Chara globularis and its relationship to calcium carbonate deposition in Malham Tarn. Field Studies 6: 53-58.

Walker, N.A., Smith, F.A. & Cathers, I.R. (1980). Bicarbonate assimilation by freshwater charophytes and higher plants: I. Membrane transport of bicarbonate ions is not proven. Journal of Membrane Biology 57: 51-58.

Wiik, E., Bennion, H., Sayer, C.D., Davidson, T.A., McGowan, S., Patmore, I.R. & Clarke, S.J. (2015). Ecological sensitivity of marl lakes to nutrient enrichment: Evidence from Hawes Water, UK   Freshwater Biology 60: 2226-2247.

Wiik, E., Bennion, H., Sayer, C.D., Davidson, T.A., Clarke, S.J., McGowen, S., Prentice, S., Simpson, G.L. & Stone, L. (2015). The coming and going of a marl lake: multi-indicator palaeolimnology reveals abrupte cological change and alternative views of reference conditions.  Frontiers in Ecology and Evolution 3:82. doi: 10.3389/fevo.2015.00082.

Costing the earth’s pantomime villain …

Some of the themes I wrote about in recent blogs came together in the latest edition of BBC Radio 4’s Costing the Earth , which unpacked the issue of river water quality and, in particular, the pernicious effects of nitrogen and phosphorus on aquatic ecosystems.   Overall, I thought that the program did a good job of explaining a complicated issue but it also served as a case study of the issues I wrote about in “Wide Sargassum Sea …”: algae are forever portrayed in the media as if they were A Bad Thing. Paul Knight, Chief Executive of Salmon and Trout Conservation UK, interviewed during the program, described algae in the River Itchen as “… a brown sort of claggy stuff …” and then went on to explain that excessive nutrients “… speed up the growth of algae and the wrong sort of weed”. From which I infer that there is a right sort of weed, but that all algae are universally bad?   Pedantic? Maybe …

However, a few minutes later we hear John Slader, also associated with Salmon and Trout Conservation UK, bemoaning the lack of invertebrate life in the River Itchen: “You’ve got to recognise that this is part of a food chain and if these insects aren’t there, what would happen to your swallows, your martins, your wagtails …”   The same subtle (or careless) omission: the food chain, of course, extends down to the algae as well as upwards to fish and birds. Successful restoration of chalk streams needs to be based on an understanding of the right sort of algae, as these ultimately create the habitat within which the insects and fish will thrive.

Later in the same programme, Mike Bowes of the Centre for Ecology and Hydrology was interviewed and he pointed out some of the practical problems associated with reducing nutrient concentrations to levels that would reduce the quantities of algae, based on the fine research he has performed over many years in southern England.   He then went on to echo some of the points I made in my previous post, “An embarrassment of riches …”: it is possible to reduce the quantities of algae not just by reducing nutrients but also by planting bankside trees in order to create more shade. This would, incidentally, have bonus effects for wildlife and aquatic diversity, and would undoubtedly be much cheaper than removing nutrients.   We should, however, remember that this may reduce the risk of eutrophication although the hazard that the nutrients presented would remain.

The program did a good job of presenting the complexity of river pollution and therein lies the challenge: if a problem is complex, there will not be straightforward cause-effect relationships.   It should not, perhaps, surprise us that the interviewees representing the pressure group were the ones that simplified the story to a cause-effect relationship (“high nutrients = bad fishing and fewer birds”) whilst the independent academic scientist offered a more nuanced view.   And it is perhaps inevitable that algae, the most diverse component of the river ecology story (see “The sum of things …”) are overlooked except when the narrative demands a convenient villain.

Reference

Bowes, M.J., Ings, N.L., McCall, S.J., Warwick, A.,Barrett, C., Wickham, H.D., Harman, S.A., Armstrong, L.K., Scarlett, P.M., Roberts, C., Lehmann, K., Singer, A.C. (2012). Nutrient and light limitation of periphyton in the River Thames: implications for catchment management. Science of the Total Environment 434: 201-212.

An embarrassment of riches …

A couple of years ago, on a snowy day in January, I gave a talk and ran a practical on algal-based ecological assessment for an MSc class at the University of Bristol. As part of the practical class, I asked my colleague, Marian Yallop, who organised the session, if she could set some algal cultures growing a few days ahead of my arrival, in order to stimulate some discussion amongst the students on what we understood by “eutrophication”.

I asked for four flasks, each with a standard algal growth media, into which an inoculum of algae was pipetted. I can’t remember what species of algae we used, except that it was a common green algae.   The growth medium was naturally low in nutrients, so Marian augmented the media in two of the flasks with an extra squirt of nutrients, so we had two with “background” nutrients and two with high nutrients.   Then she placed one of each pair on a windowsill, and the other in a refrigerator and left them for a few days.

eutrophication_thought_expe

Our eutrophication “thought experiment” in Bristol in January 2013

I had given the students the following definition of eutrophication, used in a key EU Directive (the Urban Waste Water Treatment Directive): “the enrichment of water by nutrients, especially compounds of nitrogen and/or phosphorus, causing an accelerated growth of algae and higher forms of plant life to produce an undesirable disturbance to the balance of organisms present in the water and to the quality of the water concerned.”

My question to the students was simple.   Which of the four flasks is “eutrophic”?   The first part of the definition says “the enrichment of water by nutrients …”, so we could have argued that both of the “plus nutrient” treatments were eutrophic. However, the definition then goes on to say “… causing accelerated growth of algae ….”.   The plus nutrient treatment that was kept in the refrigerator did not fulfil this criterion; however, the one kept on the window ledge is the greenest of all the flasks. So could we claim that only the “plus nutrient, window ledge” flask was eutrophic?

What about the “minus nutrient window ledge” flask?   That looked quite green, even though the nutrient levels were low.   This illustrates a further important point: the quantity of phosphorus, in particular, that a plant needs to grow is very small and if other conditions are right (i.e. a windowsill in a centrally-heated laboratory), then you can get high biomasses of algae, even without excess nutrients (see “A brief excursion to Norway”).   In nature, such natural abundance would not last for long: it would be scoured away by a flood or eaten by hungry invertebrates on the river or lake bed. Based on my experience of northern English rivers, I would only get concerned if the high biomass persisted beyond a few weeks.

The flask with added nutrients that was kept in the refrigerator offers another perspective. Even if we could argue that it is not strictly “eutrophic”, we should acknowledge that there is a risk of a high biomass developing.   In our thought experiment, the cool dark environment of the refrigerator minimised the risk of a high biomass developing.   However, for as long as there are elevated nutrient concentrations, we have to acknowledge that both “plus phosphorus” treatments represent a hazard to healthy ecosystem functioning.

A final, and slightly pedantic, interpretation was that none of these treatments fulfilled the final criterion in the definition of causing “… an undesirable disturbance to the balance of organisms …”. In this case, of course, there was only a single organism present, so it was impossible to demonstrate this particular criterion. However, a quick scan of the literature on eutrophication does show a strong bias towards establishing a link between nutrients and aquatic plants and algae, and the secondary effects are often neglected.   These, however, provide the essential “so what?” to our arguments.   I live in a world of algae-obsessed nerds and we sometimes need a sharp poke in the ribs to be reminded that most people need a better return on the expensive investment in better water treatment than just to be told that the algae have changed (see “So what?”).

Fertile speculations …

The River Browney does not give up it’s secrets gracefully.   To reach the lower stretches of this tributary of the River Wear, just a few kilometres outside Durham City I had to push through thick growths of Himalayan Balsam, stinging nettles, brambles and what looked suspiciously like Giant Hogweed.   The bankside luxuriance continued in the river itself, the bed of which is almost completely covered with either submerged water crowfoot or algae.   The river has wound its way down from the foothills of the Pennines, collecting the wastewater from small towns and, just a couple of kilometres upstream from where I stand, from a sewage works serving a large village on the outskirts of Durham itself.   The algae and plants all thrive in the steady supply of dilute manure that these works provide.

Browney_Low_Burnhall

The River Browney at Low Burnhall Nature Reserve, just below the A167 Bridge.  Photographed in September 2013.

Many of the stones in the margins were coated with brownish filaments, waving gently in the current.  When I pick up one of the stones, these filaments collapsed into amorphous slimy masses but, under the microscope, they resolved themselves into a tangle of chains of algal cells.  Two types predominated, both with the yellow-brown colouration typical of diatoms.   The most abundant of these was chains of cylinder-shaped cells.  This was Melosira varians, a very common diatom in nutrient-rich rivers and which often forms these long brown streamers during periods of low flow during the summer.   The other type of cell was cigar-shaped when seen from above (as in fig. d, below) but rectangular when seen from the side (as in fig. c.).  These cells were mostly joined at the corners to form zig-zag chains.  You can also see, in fig. d., the transverse ribs of silica which are characteristic of this genus of diatoms.

Browney_Melosira_#1

Filamentous growths of diatoms on stones in the River Browney, County Durham, September 2013 and (inset) one of the growths on a stone removed from the stream bed.

Browney_diatoms

Microscopic views of diatoms (and a few desmids) from the River Browney, September 2013.  a. low power view of the filaments; b. part of a chain of cells of Melosira varians photographed at high magnification.  Note the large number of small brown chloroplasts inside each cell (scale bar: 10 micrometres = 1/100th of a millimetre); c. zig-zag chain of Diatoma vulgare photographed at medium magnification; d. a single cell of D. vulgare at high magnification (scale bar as for b.)

These masses of cells are the microscopic equivalent of the bankside vegetation that I had to push through in order to reach the river in the first place.  The surprise was that I did not find a large number of insect larvae feasting on this abundance, as I have described from cleaner rivers such as the River Ehen.  The answer, suggested by some recent papers, is that the normal relationship between algae and their grazers breaks down in these enriched rivers.   The dense diatom growths can suck the oxygen out of the water at night when there is no sun to generate photosynthesis so the insects that would normally be feeding on the algae cannot survive.  This, in turn, will reduce the food supply of fish, as well as smothering the areas where they would normally lay their eggs.   We see, in other words, a “domino effect” as the consequences of artificially high nutrients clatter through the different groups of organisms leading, in some cases, to consequences for the way in which we are able to use these ecosystems.